A conventional software error prediction system analyzes volumes of information gathered from across an entire system for patterns in sequences of events documented in the gathered information. The conventional software error prediction systems uses the patterns to predict potential future problems. The pattern analysis can involve machine learning techniques.
Conventional security breach alerting systems also analyze volumes of information gathered from across an entire system. The analysis involves determining security breaches in one part of the system that the perpetrators may launch against another part of the system or even against a different system.
With both types of systems, information technology specialists are informed about the problems. Both types of systems rely on gathering extensive information across the entire system in order to detect errors in one part of the system and to determine whether those errors apply to other parts of the system. Both types of systems also rely on real time notification of the determined problems. Both types of systems rely on taking action in one part of a system based on a problem that was determined for another part of the system. Various types of error systems also rely on modifying applications in the system to provide information describing errors.